A spatiotemporal ensemble model to predict gross beta particulate radioactivity across the contiguous United States

High-resolution national radon maps based on massive indoor measurements in the United States

Radon, a common radioactive indoor air pollutant, is the second leading cause of lung cancer in the United States. Knowledge about its distribution is essential for risk assessment and designing efficient protective regulations. However, the three current radon maps for the United States are unable to provide the up-to-date, high-resolution, and time-varying radon concentrations. Tens of millions of radon measurements have been conducted as parts of property inspections in the past two decades, making it possible for us to improve the national radon map. We compiled a national database of over 6 million radon measurements conducted by independent laboratories during 2001 to 2021. A random forest model was built to predict monthly community-level radon concentrations based on nearly 200 geological, meteorological, architectural, and socioeconomical factors. Our radon map can accurately show the distribution of radon at higher spatial and temporal resolutions. We observed slight decreases in average radon concentrations in high-radon regions during the study period. But over 83 million people are living in residences with radon concentrations at screening floor over 148 Bq/m3 (the recommended action level). Most of these residences are in low-radon zones, highlighting the need for comprehensive radon surveys. The high-resolution radon maps can be used by federal and local governments to design, update, and improve the regulations. Furthermore, the model can be used to assess residential exposure to radon, thus facilitating studies to expand our understanding of radon's health effects.

Ambient beta particle radioactivity and lung cancer survival: Results from the Boston Lung Cancer Study

BACKGROUND

Exposure to ionizing radiation is known to increase the risk of lung cancer. However, studies on the effect of environmental radiation associated with ambient particle air pollution on lung cancer survival are limited. We investigated the association between ambient beta particle radioactivity (PR-β) after a diagnosis and lung cancer survivals.

METHODS

The Boston Lung Cancer Survival (BLCS) cohort consisted of histologically confirmed patients enrolled at Massachusetts General Hospital (MGH) and the Dana-Farber Cancer Institute (DFCI) in Boston, U.S. The primary outcomes included overall survival, 5-year survival, and 3-year survival probability. We estimated ambient PR-β exposure at the ZIP code of residence from 2001 through 2017. Cox-proportional hazards models were constructed to estimate hazard ratios (HRs) for the associations between ambient PR-β and survival outcomes while controlling for covariates.

RESULTS

The analysis included 2795 patients with complete information, with 97,330 person-months of follow-up. The interquartile range (IQR) increase in PR-β was significantly associated with worse overall survival (HR:1.63, 95% CI:1.52, 1.76), 5-year survival (HR:1.33, 95% CI:1.23, 1.44), and 3-year survival (HR:1.22, 95% CI:1.12, 1.33) while adjusting for covariates, including age at diagnosis, sex, race, smoking, stage, histology, and adjusted gross income. Similar associations were found while additionally adjusting for the estimated residential radon exposure. In addition, the survival associated with PR-β exposure was significantly worse for patients in the early stages (HR:2.16, 95% CI:1.84, 2.52).

CONCLUSION

The findings from this study provide new evidence suggesting that environmental exposure to radioactive particles after lung cancer diagnosis may have a pronounced effect on survival, particularly in patients with early stages.

Airborne particle radioactivity during desert dust days in Cyprus

Mediterranean countries are often affected by desert dust storms, which have significant effects on the environment and public health. We compared airborne particle radioactivity levels during desert dust and non-dust days in Cyprus. Gross α- and β-radioactivity from Total Suspended Particle (TSP) samples, collected at two urban routine monitoring stations in Limassol and Nicosia, were available for the period 2017-2020 and 2008-2020, respectively. Radionuclides 137Cs and 40K, from TSP samples, were also available from a semi-industrial monitoring station in Nicosia during 2008-2020. Information on desert dust presence, dust origin, particulate matter (PM) levels, and solar activity (KP index and solar sunspot numbers - SSN) were also obtained. We used linear regression models adjusting for seasonality and long-term trends, and solar activity to assess the effect of dust storms on TSP gross α- and β-, and 137Cs and 40K radioactivity levels. Gross α- and β-radioactivity, and 137Cs and 40K radioactivity levels were significantly higher on days with desert dust compared to days characterized with no influence of desert dust. Levels of gross α- and β-radioactivity during dust days were higher when dust originated from the Middle East deserts than from the Sahara Desert. The same trend was observed for the ratios 137Cs to 40K and 137Cs to PM10. Conversely, ratios of TSP gross α- and β-radioactivity to PM10 were significantly lower during desert dust days in comparison to days without dust influence. This study suggests that desert dust increase both TSP gross α- and β-radioactivity, as well as 137Cs and 40K radioactivity levels. Further studies should clarify the contribution of anthropogenic and other natural sources to the emission or transportation of particles radioactivity, to better mitigate future exposures.

Predicting Monthly Community-Level Radon Concentrations with Spatial Random Forest in the Northeastern and Midwestern United States

In 1987, the United States Environmental Protection Agency recommended installing a mitigation system when the indoor concentration of radon, a well-known carcinogenic radioactive gas, is at or above 148 Bq/m3. In response, tens of millions of short-term radon measurements have been conducted in residential buildings over the past three decades either for disclosure or to initially evaluate the need for mitigation. These measurements, however, are currently underutilized to assess population radon exposure in epidemiological studies. Based on two relatively small radon surveys, Lawrence Berkeley National Laboratory developed a state-of-the-art national radon model. However, this model only provides coarse and invariant radon estimations, which limits the ability of epidemiological studies to accurately investigate the health effects of radon, particularly the effects of acute exposure. This study involved obtaining over 2.8 million historical short-term radon measurements from independent laboratories. With the use of these measurements, an innovative spatial random forest (SRF) model was developed based on geological, architectural, socioeconomical, and meteorological predictors. The model was used to estimate monthly community-level radon concentrations for ZIP Code Tabulation Areas (ZCTAs) in the northeastern and midwestern regions of the United States from 2001 to 2020. Via cross-validation, we found that our ZCTA-level predictions were highly correlated with observations. The prediction errors declined quickly as the number of radon measurements in a ZCTA increased. When ≥15 measurements existed, the mean absolute error was 24.6 Bq/m3, or 26.5% of the observed concentrations (R2 = 0.70). Our study demonstrates the potential of the large amount of historical short-term radon measurements that have been obtained to accurately estimate longitudinal ZCTA-level radon exposures at unprecedented levels of resolutions and accuracy.

Long-term association of air pollution and incidence of lung cancer among older Americans: A national study in the Medicare cohort

BACKGROUND

Despite strong evidence of the association of fine particulate matter (PM2.5) exposure with an increased risk of lung cancer mortality, few studies had investigated associations of multiple pollutants simultaneously, or with incidence, or using causal methods. Disparities were also understudied.

OBJECTIVES

We investigated long-term effects of PM2.5, nitrogen dioxide (NO2), warm-season ozone, and particle radioactivity (PR) exposures on lung cancer incidence in a nationwide cohort.

METHODS

We conducted a cohort study with Medicare beneficiaries (aged ≥ 65 years) continuously enrolled in the fee-for-service program in the contiguous US from 2001 to 2016. Air pollution exposure was averaged across three years and assigned based on ZIP code of residence. We fitted Cox proportional hazards models to estimate the hazard ratio (HR) for lung cancer incidence, adjusted for individual- and neighborhood-level confounders. As a sensitivity analysis, we evaluated the causal relationships using inverse probability weights. We further assessed effect modifications by individual- and neighborhood-level covariates.

RESULTS

We identified 166,860 lung cancer cases of 12,429,951 studied beneficiaries. In the multi-pollutant model, PM2.5 and NO2 exposures were statistically significantly associated with increased lung cancer incidence, while PR was marginally significantly associated. Specifically, the HR was 1.008 (95% confidence interval [CI]: 1.005, 1.011) per 1-μg/m3 increase in PM2.5, 1.013 (95% CI: 1.012, 1.013) per 1-ppb increase in NO2, and 1.005 (0.999, 1.012) per 1-mBq/m3 increase in PR. At low exposure levels, all pollutants were associated with increased lung cancer incidence. Men, older individuals, Blacks, and residents of low-income neighborhoods experienced larger effects of PM2.5 and PR.

DISCUSSION

Long-term PM2.5, NO2, and PR exposures were independently associated with increased lung cancer incidence among the national elderly population. Low-exposure analysis indicated that current national standards for PM2.5 and NO2 were not restrictive enough to protect public health, underscoring the need for more stringent air quality regulations.

Associations of solar activity and related exposures with fetal growth

BACKGROUND

Solar and geomagnetic activity have been shown to suppress melatonin and to degrade folate levels, important hormones for fetal development. We examined whether solar and geomagnetic activity were associated with fetal growth.

METHODS

We included 9573 singleton births with 26,879 routine ultrasounds at an academic medical center in Eastern Massachusetts from 2011 through 2016. Sunspot number and Kp index were obtained from the NASA Goddard Space Flight Center. Three exposure windows were considered, including the first 16 weeks of pregnancy, one month prior to fetal growth measurement, and conception until fetal growth measurement (cumulative). Ultrasound scans from which we extracted biparietal diameter, head circumference, femur length, and abdominal circumference measurements were categorized as anatomic (<24 weeks' gestation) or growth scans (≥24 weeks' gestation) based on clinical practice. Ultrasound parameters and birth weight were standardized, and linear mixed models adjusted for long-term trends were fitted.

RESULTS

Prenatal exposures were positively associated with larger head parameters measured <24 weeks' gestation, negatively associated with smaller fetal parameters measured ≥24 weeks' gestation, and not associated with birth weight. The strongest associations were observed for cumulative exposure in growth scans, where an interquartile range increase in sunspot number (32.87 sunspots) was associated with a -0.17 (95 % CI: -0.26, -0.08), -0.25 (-0.36, -0.15), and -0.13 (95 % CI: -0.23, -0.03) difference in mean biparietal diameter, head circumference, and femur length z-score, respectively. An interquartile range increase in cumulative Kp index (0.49) was associated with a -0.11 (95 % CI: -0.22, -0.01) and -0.11 (95 % CI: -0.20, -0.02) difference in mean head circumference and abdominal circumference z-score, respectively, in growth scans.

CONCLUSIONS

Solar and geomagnetic activity were associated with fetal growth. Future studies are needed to better understand the impact of these natural phenomena on clinical endpoints.

Prenatal Exposure to Ambient Particle Radioactivity and Fetal Growth in Eastern Massachusetts

Background

The radioactive component of particulate matter (PM), particle radioactivity (PR), can continue to emit radiation after inhalation. While PR has been associated with other adverse pregnancy outcomes, no studies have examined the association with fetal growth.

Methods

Our retrospective cohort included singleton pregnancies that underwent obstetric ultrasounds at an academic medical center in Massachusetts from 2011 through 2016. PR was represented by particle gross β-activity estimated from an ensemble model and was assigned based on residential zip-code. We considered the cumulative (conception until date of fetal growth measurement) and first 16 weeks of gestation PR exposure windows. Standardized z-scores were constructed for biparietal diameter (BPD), head circumference, femur length (FL), abdominal circumference (AC), and birth weight. We used linear mixed regression models adjusted for PM ≤2.5 μm exposure, maternal sociodemographic factors, meteorological variables, and long-term trends.

Results

Among 9,404 pregnancies, an interquartile range increase in cumulative PR exposure was associated with reduced BPD (-0.06 [95% CI: -0.12, -0.01] z-score) and FL (-0.06 [95% CI: -0.12, -0.01] z-score) in scans conducted before 24 weeks' gestation, with increased AC (0.05 [95% CI: 0.01, 0.09]) in scans conducted on or after 24 weeks' gestation, and with lower birth weight (-0.05 [95% CI: -0.11, -0.001] z-score). The first 16 weeks of gestation was not a critical exposure window.

Conclusions

Prenatal PR was associated with fetal growth, with associations generally negative before 24 weeks' gestation and positive later in pregnancy. Our findings bring awareness to a novel environmental exposure.

Patterns of indoor radon concentrations, radon-hazard potential, and radon testing on a small geographic scale in Utah

INTRODUCTION

Currently, there are no publicly-available estimates of indoor radon concentration at scales smaller than the county. Radon-hazard potential soil maps that reflect underlying geologic factors can be created at small geographic scale and linked to residential and census data. We determined the association between residential radon tests and high radon-hazard potential soil at the residential and block group levels using a large Utah-based dataset. We also identified characteristics of block groups with limited tests in the dataset.

METHODS

We geocoded a dataset of residential radon tests obtained from 2001 to 2017 by a statewide educational program. We linked each location to maps of radon-hazard potential soil, the Environmental Protection Agency's (EPA) county radon zones. We also calculated the number of tests conducted in each block group and linked block groups to demographic data from the 2020 United States census. Log-linear and logistic models identified the association between residential home test results and 1) radon-hazard potential soil of each residence, 2) percent of residences on high radon-hazard potential soils in block groups, and 3) EPA's radon zones. We compared demographic characteristics among block groups with ≥5 or <5 residential tests in our dataset.

RESULTS

Approximately 42% of homes in the dataset tested ≥4 pCi/L. We found significant positive associations for residential radon test results with 1) residential location on high radon-hazard potential soil and 2) block groups with >0% of residences on high radon-hazard potential soil. EPA radon zones were not associated with residential test results. Block groups with <5 tests had higher than the statewide median percentage of Hispanic residents (OR = 2.46, 95% CI = 1.89-3.21) and were located in rural counties.

DISCUSSION

Radon-hazard potential soil has a significant association with residential home radon tests. More efforts are needed to improve radon testing in block groups that are rural and have greater percentages of racial minorities.

Synergistic Effects of Particle Radioactivity (Gross β Activity) and Particulate Matter ≤2.5 μm Aerodynamic Diameter on Cardiovascular Disease Mortality

Background Although the effects of fine particulate matter (particulate matter ≤2.5 μm aerodynamic diameter [PM2.5]) on cardiovascular disease (CVD) morbidity and mortality are well established, little is known about the CVD health effects of particle radioactivity. In addition, there are still questions about which of the PM2.5 physical, chemical, or biological properties are mostly responsible for its toxicity. Methods and Results We investigated the association between particle radioactivity, measured as gross β activity from highly resolved spatiotemporal predictions, and mortality for CVD, myocardial infarction, stroke, and all-cause nonaccidental mortality in Massachusetts (2001-2015). Within both difference-in-differences model and generalized linear mixed model frameworks, we fit both single-exposure and 2-exposure models adjusting for PM2.5 and examined the interaction between PM2.5 and gross β activity. We found significant associations between gross β activity and PM2.5 and each mortality cause. Using difference-in-differences and adjusting for PM2.5, we found the highest associations with myocardial infarction (rate ratio, 1.16 [95% CI, 1.08-1.24]) and stroke (rate ratio, 1.11 [95% CI, 1.04-1.18]) for an interquartile range increase (0.055 millibecquerels per cubic meter) in gross β activity. We found a significant positive interaction between PM2.5 and gross β activity, with higher associations between PM2.5 and mortality at a higher level of gross β activity. We also observed that the associations varied across age groups. The results were comparable between the 2 statistical methods also with and without adjusting for PM2.5. Conclusions This is the first study that, using highly spatiotemporal predictions of gross β-activity, provides evidence that particle radioactivity increases CVD mortality and enhances PM2.5 CVD mortality. Therefore, particle radioactivity can be an important property of PM2.5 that must be further investigated. Addressing this important question can lead to cost-effective air-quality regulations.